W4-Groups: Modeling the Who, What, When and Where of Group Behavior via Mobility Sensing
Atrey, A., Zakaria, C., Balan, R., & Shenoy, P.
CSCW 2024 | Proceedings of the ACM on Human-Computer Interaction (To appear)

BreathEasy: Exploring the Potential of Acoustic Sensing for Healthy Indoor Environments
Chagglani, B., Zakaria, C., Gummeson, J., & Shenoy, P.
EnvSys (MobiSys, Workshop) 2023| Proceedings of the 1st International Workshop on Advances in Environmental Sensing Systems for Smart Cities
| pdf|

SleepMore: Inferring Sleep Duration at Scale with Multi-Device WiFi Sensing
Zakaria, C., Yilmaz, G., Mammen, P., Chee, M., Shenoy, P., & Balan, R.
IMWUT (UbiComp) 2023| Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
| pdf|

Does Mode of Digital Contact Tracing Affect User Willingness to Share Information? A Quantitative Study
Zakaria, C., Foong, PS., Lim, CS., Pakianathan, V., Koh, G., & Perrault, S.
CHI 2022 | Proceedings of the ACM Conference on Human Factors in Computing Systems
| pdf|

Analyzing the Impact of COVID-19 Control Policies on Campus Occupancy and Mobility via Passive WiFi Sensing
Zakaria, C., Trivedi, A., Cecchet, E., Chee, M., Shenoy, P., & Balan, R.
TSAS 2022 | ACM Transactions on Spatial Algorithms and System. Special Issue on Contact Tracing
| pdf|

FlowSense: Monitoring Airflow in Building Ventilation Systems Using Audio Sensing
Chagglani, B., Zakaria, C., Lechowicz, A., Gummeson, J., & Shenoy, P.
IMWUT (UbiComp) 2022 | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
| pdf|

WiSleep: Inferring Sleep Duration at Scale Using Passive WiFi Sensing
Mammen, P., Zakaria, C., Molom-Ochir, T., Trivedi, A., Shenoy, P., & Balan, R.
ArXiV
| pdf|

Detection of Students' Workgroup Identification using Passively Sensed WiFi Infrastructure
Zakaria, C., Balan, R., Lee, Y.
CSCW 2021 | Proceedings of the ACM on Human-Computer Interaction
| pdf|

WiFiTrace: Network-based Contact Tracing for Infectious Diseases using Passive WiFi Sensing
Trivedi, A., Zakaria, C., Balan, R., Becker, A., Corey, G., & Shenoy, P.
IMWUT (UbiComp) 2021 | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
| pdf|

StressMon: Scalable Detection of Perceived Stress and Depression Using Passive Sensing of Changes in Work Routines and Group Interactions
Zakaria, C., Balan, R., Lee, Y.
CSCW 2019 | Proceedings of the ACM on Human-Computer Interaction
| pdf|

Exploratory Analysis of Individuals' Mobility Patterns and Experienced Conflicts in Workgroups
Zakaria, C., Goh, K., Lee, Y., & Balan, R.
MSCSS, MobiSys 2019 | Proceedings of the 5th ACM Workshop on Mobile Systems for Computational Social Science
| pdf|

A Comparative Study of Pointing Techniques for Eyewear Using a Simulated Pedestrian Environment
Roy, Q., Zakaria, C., Perrault, S., Nancel, M., Kim, W., Misra, A., & Cockburn, A.
INTERACT 2019 | 17th IFIP International Conference on Human-Computer Interaction
| pdf|

Seeking independent management of problem behavior: A proof-of-concept study with children and their teachers
Zakaria, C., Davis, R. C., & Walker, Z.
IDC 2016 | Proceedings of the The 15th International Conference on Interaction Design and Children
| pdf|

Duplicate issue detection for the Android open source project
Jayarajah, K., Radhakrishnan, M., & Zakaria, C.
SoftwareMining, KDD 2016 | Proceedings of the 5th International Workshop on Software Mining
| pdf|

K-Sketch: Digital Storytelling with Animation Sketches
Davis, R. C., & Zakaria, C.
ICIDS 2014 | Interactive storytelling: 7th International Conference on Interactive Digital Storytelling
| pdf|

Thesis: StressMon: Large Scale Detection of Stress and Depression in Campus Environment using Passive Coarse-grained Location Data
Zakaria, C.
| pdf|

How Singapore has kept the coronavirus off campus
The New York Times
Our work is the first network-side contact tracing method built to monitor user movements and co-occurrences for public health evaluation!
| link| pdf|

The campus as a laboratory, Making an Impact
BBC
| link| pdf|

Monitoring and addressing stress
Office of Research & Tech Transfer, Research@SMU Aug 2019 Issue
| link| pdf|

STRESSMON is envisioned as an ML-driven safety net to monitor stress and depression for an entire population of users. The system leverages passive WiFi information to derive group interaction features and measures the changes in an individual's behavior, including group interaction habits, by comparing their own and the population's past periods to detect stress and depression. The system has undergone three rounds of longitudinal validation among 108 college students, who regularly assessed their stress and depression using the Perceived Stress Scale (PSS) and Patient Health Questionnaire (PHQ-8). Future development of this work includes extending passive sensing capabilities to measure significant predictors of mental health, including sleep and social relationships.
| Video|

WATCHME is my first Ph.D. work, close to my heart. This work is built on sufficient progress in mobile sensing and HCI to assume that wearable devices can detect the physical movements and sounds in most problem behaviors. For example, I used the accelerometer sensor built-in commercial wearables to detect hand gestures and a microphone sensor to detect vocalizations. I hope to continue this work on building an independent behavior management tool that provides effective intervention to child users only when necessary.